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Related Questions
- What is the key difference between attention and traditional RNNs in terms of input processing?
- How does the attention mechanism allow the model to selectively focus on relevant parts of the input sequence?
- Can you explain the concept of 'weights' in the attention mechanism and how they are used to prioritize certain inputs?
- How does the attention mechanism differ from other mechanisms such as memory-augmented networks or graph neural networks?
- What are some common applications of the attention mechanism in natural language processing tasks?
- How does the attention mechanism enable the model to capture long-range dependencies in the input sequence?
- Can you provide an example of how the attention mechanism can be used to improve the performance of a machine translation model?
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